9 research outputs found

    Empirical fragility curves for settlement-affected buildings: Analysis of different intensity parameters for seven hundred masonry buildings in The Netherlands

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    The analysis and prediction of damage to buildings resting on highly compressible fine-grained "soft soils" containing (organic) clay and peat are key issues to be addressed for a proper management of subsidence-affected urban areas. Among the probabilistic approaches suggested in literature, those oriented to the generation of empirical fragility curves are particularly promising provided that a comprehensive dataset for both the subsidence-related intensity (SRI) parameters and the corresponding damage severity to buildings is available. Following this line of thought, in the present paper, a rich sample of more than seven hundred monitored (by remote sensing) and surveyed masonry buildings – mainly resting with their (shallow or piled) foundations on soft soils – is analysed in four urban areas of The Netherlands. Probabilistic functions in the form of fragility curves for building damage are retrieved for three different SRI parameters (i.e., differential settlement, rotation and deflection ratio) derived from the processing of Synthetic Aperture Radar (SAR) images by way of a differential interferometric (DInSAR) technique in combination with the severity levels of the damage recorded from the visual inspection of over 700 masonry buildings. As a novelty with respect to earlier similar studies, the work points out the methodological steps to be followed in order to identify the most appropriate SRI parameter among the selected ones. Thus, the objective of the paper is to improve the existing geotechnical forecasting tools for subsidence-affected urban areas, in order to target areas that require more detailed investigations/analyses and/or to select/prioritize foundation repairing/replacing measures

    Database of subsidence in major coastal cities around the world

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    This database aims to be an open-source, accurate, peer-reviewed and comprehensive database of coastal cities currently experiencing land subsidence and its main and secondary causes. It aims to facilitate future research regarding subsidence in both priorly identified at-risk areas and in areas where the potential impact of subsidence is still unknown. The selection of the cities is based on the following papers: · Nicholls, R. J. (2008). The Exposure of Port Cities to Flooding: A Comparative Global Analysis. · Hallegatte, S., Green, C., Nicholls, R. J., & Corfee-Morlot, J. (2013). Future flood losses in major coastal cities. Nature climate change, 3(9), 802-806. · Solari, L., Del Soldato, M., Bianchini, S., Ciampalini, A., Ezquerro, P., Montalti, R., ... & Moretti, S. (2018). From ERS 1/2 to Sentinel-1: subsidence monitoring in Italy in the last two decades. Frontiers in Earth Science, 6, 149.This work was developed in the framework of the project RESERVOIR (sustainable groundwater RESources managEment by integrating eaRth observation deriVed monitoring and flOw modelIng Results) funded by the Partnership for Research and Innovation in the Mediterranean Area (PRIMA) programme supported by the European Union (Grant Agreement 1924; https://reservoir-prima.org/)

    Using discrete choice experiments to inform randomised controlled trials:an application to chronic low back pain management in primary care

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    Pain Management Programmes (PMPs) are a multi-disciplinary approach to the management of chronic low back pain (CLBP). Notwithstanding evidence of effectiveness, successful take-up of programmes requires acceptability to patients. We used a discrete choice experiment to investigate patient preferences for alternative PMPs for managing CLBP in primary care. Specifically, we estimated the probability of uptake of alternative configurations of PMPs. Potential attributes and associated levels influencing take-up were identified through a systematic literature review, survey of current PMPs, expert consultation, and focus groups. Five attributes were included: content; provider; schedule; group size; and travel time to clinic. Four hundred and fourteen questionnaires were mailed to patients attending clinics and 124 questionnaires were returned suitable for analysis. Method of delivery influenced probability of take-up, with small group sizes and low intensity programmes over a prolonged period increasing the probabilities. Travel time was also important. However, providers and contents of PMPs were not main drivers of preferences, though those with more severe pain did prefer PMPs provided by more specialists. Probability of take-up increases when PMPs better reflect patient preferences. Given preferences, resource constraints, and evidence on clinical outcomes of alternative configurations it is suggested more resource-intensive PMPs be reserved for those with the most severe and disabling pain and less intensive programmes delivered over a longer time period in smaller groups for those with less severe pain. These findings can inform future randomised trials to evaluate acceptable PMPs in primary care
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